Library Analytics (Part 8)

In Library Analytics (Part 7), I posted a couple of ideas about how it might be an idea if the Library started crafting URLs for the the Library resources pages for individual courses in the Moodle VLE that contained a campaign tracking code, so that we could track the behaviour of students coming into the Library site by course.

From a quick peak at a handful of courses in the VLE, that recommendation either doesn’t appear to have been taken up, or it’s just “too hard” to do, so that’s another couple of months data we don’t have easy access to in the Google Analytics environment. (Or maybe the Library have moved over to using the OU’s SIte Analytics service for this sort of insight?)

Just to recall, we need to put some sort of additional measures in place because Moodle generates crappy URLs (e.g. URLs of the form and crafting nice URLs or using mod-rewrite (or similar) definitely is way too hard for the VLE’n’network people to manage;-) The default set up of Google Analytics dumps everything after the “?”, unless they are official campaign tracking arguments or are captured otherwise.

(From a quick scan of Google Analytics Tracking API, I’m guessing that setting pageTracker._setCampSourceKey(“id”); in the tracking code on each Library web page might also capture the id from referrer URLs? Can anyone confirm/deny that?)

Aside: from what I’ve been told, I don’t think we offer server side compression for content served from most* sites, either (though I haven’t checked)? Given that there are still a few students on low bandwidth connections and relatively modern browsers, this is probably an avoidable breach of some sort of accessibility recommendation? For example, over the lat 3 weeks or so, here’s the number of dial-up visits to the Library website:

A quick check of the browser stats shows that IE breaks down almost completely as IE6 and above; all of which cope with compressed files, I think?

[Clarification (?! heh heh) re: dial-in stats – “when you’re looking at the dial-up use of the Library website is that we have a dial-up PC in the Library to replicate off-campus access and to check load times of our resources. So it’s probably worth filtering out that IP address (***.***.***.***) to cut out library staff checking out any problems as this will inflate the perceived use of dial-up by our students. Even if we’ve only used it once a day then that’s a lot of hits on the website that aren’t really students using dial-up” – thanks, Clari :-)]

Anyway – back to the course tracking: as a stop gap, I created a few of my own reports that use a user defined argument corresponding to the full referrer URL:

We can then view reports according to this user defined segment to see which VLE pages are sending traffic to the Library website:

Clicking through on one of these links gives a report for that referrer URL, and then it’s easy to see which landing pages the users are arriving at (and by induction, which links on the VLE page they clicked on):

If we look at the corresponding VLE page:

Then we can say that the analytics suggest that the Open University Library –, the Online collections by subject – and the Library Help & Support – are the only links that have been clicked on.

[Ooops… “Safari & Info Skills for Researchers are our sites, but don’t sit within the domain ([ ] and [ ] respectively) and the Guide to Online Information Searching in the Social Sciences is another Moodle site.” – thanks Clari:-) So it may well be that people are clicking on the other links… Note to self – if you ever see 0 views for a link, be suspicious and check everything!]

(Note that I have only reported on data from a short period within the lifetime of the course, rather than data taken from over the life of the course. Looking at the incidence of traffic over a whole course presentation would also give an idea of when during the course students are making use of the Library resource page within the course.)

Another way of exploring how VLE referrer traffic is impacting on the Library website is to look at the most popular Landing pages and then see which courses (from the user defined segment) are sourcing that traffic.

So for example, here are the VLE pages that are driving traffic to the elluminate registration page:

One VLE page seems responsible:

Hmmm… ;-)

How about the VLE pages driving traffic to the ejournals page?

And the top hit is….

… the article for question 3 on TMA01 of the November 2008 presentation of M882.

The second most popular referrer page is interesting because it contains two links to the Library journals page:


Unfortunately, there’s no way of disambiguating which link is driving the tracking – which is one good reason why a separate campaign related tracking code should be associated with each link.

(Do you also see the reference to Google books in there? Heh heh – surely they aren’t suggesting that students try to get what they need from the book via the Google books previewer?!;-)

Okay – enough for now. To sum up, we have the opportunity to provide two sorts of report – one for the Library to look at how VLE sourced traffic as a whole impacts on the Library website; and a different set of reports that can be provided to course teams and course link librarians to show how students on the course are using the VLE to access Library resources.

PS if you havenlt yet watch Dave Pattern’s presentation on mining lending data records, do so NOW: Can You Dig It? A Systems Perspective.

Author: Tony Hirst

I'm a Senior Lecturer at The Open University, with an interest in #opendata policy and practice, as well as general web tinkering...